/*
 * Copyright (c) 2020-2025, NVIDIA CORPORATION.  All rights reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#pragma once

#include <cuda.h>

#include <cstdint>
#include <optional>
#include <vector>

// #include "flashinfer/trtllm/common/Dtype.h"
#include "trtllmGen_bmm_export/trtllm/gen/DtypeDecl.h"

namespace tensorrt_llm {
namespace kernels {

struct TrtllmGenBatchedGemmRunnerOptions {
  batchedGemm::trtllm::gen::Dtype eltType;
  batchedGemm::trtllm::gen::Dtype outputType;
  bool deepSeekFp8{false};
  bool fusedAct{false};
  bool routeAct{false};
  bool staticBatch{false};
  bool transposeMmaOutput{false};
  int32_t tileSize{8};
  int32_t epilogueTileM{128};
};

class TrtllmGenBatchedGemmRunner {
 public:
  explicit TrtllmGenBatchedGemmRunner(TrtllmGenBatchedGemmRunnerOptions const& options);

  [[nodiscard]] size_t getWorkspaceSizeInBytes(int32_t m, int32_t n, int32_t k,
                                               std::vector<int32_t> const& batchedTokens,
                                               int32_t numTokens, int32_t numBatches,
                                               int32_t maxNumCtasInBatchDim,
                                               int32_t configIndex) const;

  // Generic GEMM interface
  void run(int32_t m, int32_t n, int32_t k, std::vector<int32_t> const& batchedTokens,
           int32_t numTokens, int32_t numBatches, int32_t maxNumCtasInBatchDim, void const* a,
           void const* sfA, void const* b, void const* sfB, void const* perTokensSfA,
           void const* perTokensSfB, float const* scaleC, float const* scaleGateC, void* c,
           void* outSfC, int32_t const* routeMap, int32_t const* totalNumPaddedTokens,
           int32_t const* ctaIdxXyToBatchIdx, int32_t const* ctaIdxXyToMnLimit,
           int32_t const* numNonExitingCtas, void* workspace, CUstream stream, int device,
           int32_t configIndex);

  // NVFP4 per-block scaling GEMM
  void run(int32_t m, int32_t n, int32_t k, std::vector<int32_t> const& batchedTokens,
           void const* a, void const* sfA, void const* b, void const* sfB, void* c, void* outSfC,
           void* workspace, CUstream stream, int device, int32_t configIndex);

  // FP8 per-tensor scaling GEMM
  void run(int32_t m, int32_t n, int32_t k, std::vector<int32_t> const& batchedTokens,
           void const* a, void const* b, float const* scaleC, float const* scaleGateC, void* c,
           void* workspace, CUstream stream, int device, int32_t configIndex);

  // Get the list of configs that passed the validation based on the constructor options
  [[nodiscard]] std::vector<int64_t> getPassingConfigIndices() const {
    return mPassingConfigIndices;
  }

  // Get the list of config indices that are valid for the given problem shape
  [[nodiscard]] std::vector<int64_t> getValidConfigIndices(
      int32_t m, int32_t n, int32_t k, std::vector<int32_t> const& batchedTokens, int32_t numTokens,
      int32_t numBatches, int32_t maxNumCtasInBatchDim) const;

  // Get a default config index that is valid for the given problem shape
  // This will be used as the fallback config if using auto-tuning
  [[nodiscard]] int64_t getDefaultValidConfigIndex(int32_t m, int32_t n, int32_t k,
                                                   std::vector<int32_t> const& batchedTokens,
                                                   int32_t numTokens, int32_t numBatches,
                                                   int32_t maxNumCtasInBatchDim) const;

  [[nodiscard]] bool isValidConfigIndex(int32_t configIndex, int32_t m, int32_t n, int32_t k,
                                        std::vector<int32_t> const& batchedTokens,
                                        int32_t numTokens, int32_t numBatches,
                                        int32_t maxNumCtasInBatchDim) const;

 private:
  void selectGemmConfig(int32_t m, int32_t n, int32_t k, std::vector<int32_t> const& batchedTokens,
                        int32_t numTokens, int32_t numBatches, int32_t maxNumCtasInBatchDim);

 private:
  TrtllmGenBatchedGemmRunnerOptions mOptions;
  std::vector<int64_t> mPassingConfigIndices;
};
}  // namespace kernels
}  // namespace tensorrt_llm
